Recent improvements in information technology, typified by the Internet, and well-organized infrastructure have encouraged a widespread use of a vast amount of images. However, it is also true that such diversity of the usage has brought users a difficulty in retrieving a required image correctly and speedy from reams of data.
In a conventional retrieval system, a Boolean equation keyword-aided retrieval, in which keywords associated with logical operators, such as AND, OR are specified as selection criteria, has been commonly used in searching, keywords- or labels-tagged image data. With the system, an image that matches with selection criteria specified keywords associated with the Boolean equations is retrieved from as much as tens of, or even hundreds of thousands of data. In the conventional system described above, however, it is a crucial determinant how the user specifies the selection criteria effectively, using appropriate keywords with the Boolean equation. That is, it is often difficult to obtain desired results or even to set appropriate selection criteria, unless the user is familiar with a tendency of a data group filed in a database or the structure of a retrieval system. To find out a tendency, it may be necessary to understand the keywords of the data group are defined on what kind of conditions. Likewise, to have a good grasp of the structure of a retrieval system, it may be important to be aware whether or not the retrieval system covers thesauruses, to which the entered keywords correspond.
For such reasons, it has often been difficult for a beginner to obtain intended information or distribution.
In addition, in such retrieval system, the obtained result is evaluated for the simple reason that the result matches a Boolean equation with specified keywords. That is, it is often occurred that the result happens to match with the specified keyword and, in reality, the obtained result disappointedly turned to be unwanted one. Interrupted with such inconveniences, it is not easy to select much-needed information for an individual user from long lists of the obtained results in order of precedence.